Data Engineer Intern (E-commerce) - 2027 Summer
TikTok
- Location
- San Jose, California, United States of America
- Employment
- Internship
- Work model
- On-Site
- Level
- Intern
- H-1B history
- 148 approvals (FY2023)
Skills
About this role
As a data engineer in the Data Platform E-Commerce team, you will have the opportunity to build, optimize and grow one of the largest data platforms in the world. You'll have the opportunity to gain hands-on experience on all kinds of systems in the data platform ecosystem. Your work will have a direct and huge impact on the company's core products as well as hundreds of millions of users.
We are actively exploring how to deeply integrate traditional search engine technologies with Large Language Models (LLMs) to enhance the TikTok Search experience and pioneer new search paradigms. You will have the opportunity to work on challenging problems at the intersection of information retrieval, machine learning, natural language understanding, recommendation systems, and large-scale distributed systems.
We are looking for talented individuals to join us for an internship. Our internship program offers students hands-on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth. Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals. Candidates may apply to a maximum of two positions across Our Company and its affiliates globally. Applications will be considered in the order they are submitted. Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates.
Candidates who pass resume screening will be invited to participate in Our Company's technical online assessment.
Responsibilities - What You'll Do - Design and build data transformations efficiently and reliably for different purposes (e.g. reporting, growth analysis, multi-dimensional analysis); - Design and implement reliable, scalable, robust and extensible big data systems that support core products and business; - Establish solid design and best engineering practice for engineers as well as non-technical people.